In this post, Dr. Fernández-Barrera describes new, innovative methods of analyzing very large quantities of law-related user-generated content.

In two recent studies described in the post, Dr. Fernández-Barrera and colleagues analyzed thousands of consumer law queries and complaints submitted by citizens to consumer protection agencies in Spain and Italy. Using a combination of automated text extraction techniques and expert input from lawyers, the researchers mapped the citizens’ lay terminology to formal legal terms. The technical legal language was expressed in legal ontologies — the Mediation Core Ontology and the Consumer Mediation Ontology — or in statutes: the Italian Consumer Code. The results of this research give us new insights about citizens’ knowledge of consumer law, and about the relationships between formal legal language and the way law is expressed in lay language.

Dr. Fernández-Barrera then describes her recent research into methods for making legal semantic analysis of user-generated content scalable. In studies of citizens’ online queries about consumer law and noise-nuisance complaints, she and her colleagues found that by focusing on language patterns involving emotions, events, and “stereotypical situations appearing in the description of legal cases by citizens,” automated techniques alone could successfully analyze very large quantities of user-generated content. Dr. Fernández-Barrera concludes by reflecting on the ethical dimensions of governments’ use of citizen comments in law- and policy making.

This post should be of interest to policy makers, the e-government and Government 2.0 communities, the Web 2.0 community, those who study legal language, and developers of legal information systems.